Sequential Purchase Recommendation System for E-Commerce Sites

Abstract : To find out which product should be recommended to the customer and when to recommend is done by the recommender system. Different approaches by using customer profile and product description are used to build recommender system. Although these information are not enough to recommend, sometimes buying of some products occurs in a stepwise manner, where buying of one product follows the buying of other products. The purpose of this research is to find the sequences followed by customers while purchasing products to improve the efficiency of recommender system. Sequence pattern mining is used to find out the order of purchasing products. The duration we find tells the time gap between the purchased product and recommendation of next sequential products.
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Khalid Saeed; Władysław Homenda; Rituparna Chaki. 16th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM), Jun 2017, Bialystok, Poland. Springer International Publishing, Lecture Notes in Computer Science, LNCS-10244, pp.366-375, 2017, Computer Information Systems and Industrial Management. 〈10.1007/978-3-319-59105-6_31〉
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Soumis le : mardi 5 décembre 2017 - 14:56:34
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Shivani Saini, Sunil Saumya, Jyoti Singh. Sequential Purchase Recommendation System for E-Commerce Sites. Khalid Saeed; Władysław Homenda; Rituparna Chaki. 16th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM), Jun 2017, Bialystok, Poland. Springer International Publishing, Lecture Notes in Computer Science, LNCS-10244, pp.366-375, 2017, Computer Information Systems and Industrial Management. 〈10.1007/978-3-319-59105-6_31〉. 〈hal-01656206〉

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